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WO2009092017A1 - Marqueurs biologiques pour le cancer induit par le hpv - Google Patents

Marqueurs biologiques pour le cancer induit par le hpv Download PDF

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Publication number
WO2009092017A1
WO2009092017A1 PCT/US2009/031302 US2009031302W WO2009092017A1 WO 2009092017 A1 WO2009092017 A1 WO 2009092017A1 US 2009031302 W US2009031302 W US 2009031302W WO 2009092017 A1 WO2009092017 A1 WO 2009092017A1
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WIPO (PCT)
Prior art keywords
cervical
biomarkers
cells
levels
cytokeratin
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PCT/US2009/031302
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English (en)
Inventor
William Dynan
Hilal Arnouk
Mark Merkley
Jeffrey Lee
Daron Ferris
Hubert Stoppler
Robert H. Podolsky
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Medical College Of Georgia Research Institute, Inc.
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Application filed by Medical College Of Georgia Research Institute, Inc. filed Critical Medical College Of Georgia Research Institute, Inc.
Priority to US12/745,404 priority Critical patent/US20100316990A1/en
Publication of WO2009092017A1 publication Critical patent/WO2009092017A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • G01N33/57411—Specifically defined cancers of cervix

Definitions

  • the invention is generally related to the field of oncology, in particular, to biomarkers for cervical cancer.
  • the Pap test has shortcomings. Abnormal or ambiguous findings, which occur in about 3 million of the 55 million Pap smears performed annually in the US, necessitate costly and sometimes invasive follow-up.
  • the accuracy of the Pap test has been studied extensively, and meta-analysis indicates that high specificity and sensitivity cannot be achieved concurrently [5], Classification of both Pap smears and follow-up biopsies is subject to high inter-observer variability, with agreement on grading of biopsy specimens only 40% to 80% more than expected by chance alone [6].
  • the natural history of cervical premalignant lesions shows great individual variability.
  • HPV DNA assays have been shown to be preferable to repeat cytology [12]
  • Surrogate protein markers for HPV infection have also been used, including high-level expression of the cyclin-dependent kinase inhibitor, pl6(Ink4a), and the expression of a marker of cell proliferation, Ki-67, in normally non-dividing cells of the upper layers of the epithelium [13-15].
  • HPV or surrogate markers for diagnosis is that infection with high-risk type HPV is relatively common (point prevalence - 3.4% [16]) and many infections clear spontaneously. It would be useful to have a test to detect the transition from infected cells, which proliferate simply in response to viral oncoprotein expression, and virally transformed cells, which have accumulated additional genetic and epigenetic changes during a latency period. There are currently no clinically useful molecular markers for detecting this transition.
  • biomarkers for detecting the transition of virally infected cells to virally transformed cells in HPV-induced cancer.
  • Biomarkers that correlate with progression to neoplasia in human papillomavirus (HPV) induced cancer, for example cervical cancer have been identified. These biomarkers can be used to diagnosis or assist in the diagnosis of HPV-induced cancer. They can also be used to increase the positive predictive value of current screening modalities. In addition, they can provide insights into the biology of HPV-induced cancer and thus provide leads for the development of nonsurgical therapies.
  • HPV human papillomavirus
  • biomarkers include cornulin, PA28 ⁇ , DJ-I, actin, transthyretin, HSPBl, Cl " intracellular channel I 5 cytokeratin 8, transferrin, Hsp ⁇ 6 (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, creatine kinase B, cytokeratin 13 GST ⁇ , PA28 ⁇ , Manganese SOD, lamin A/C, serpin Bl (elastase inhibitor), serpin B3 (SCAAl), cytokeratin 10, cytokeratin 6A, and trp-tRNA synthetase.
  • Preferred biomarkers for HPV-induced cancer include cornulin, DJ-I, PA28 ⁇ , and PA28 ⁇ , trp-tRNA synthetase, HSP ⁇ 6, creatine kinase B, aflatoxin reductase, GST ⁇ , transthyretin, transferrin, ⁇ 2-ty ⁇ e 1 collagen, and combinations thereof.
  • HPV-induced cancer selected from the group consisting of cornulin, P A28 ⁇ , DJ-I, actin, transthyretin, HSPBl, Cl " intracellular channel I 5 cytokeratin 8, transferrin, Hsp ⁇ 6 (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, creatine kinase B, cytokeratin 13, GST ⁇ , PA28 ⁇ , Manganese SOD, lamin A/C, serpin Bl (elastase inhibitor), serpin B3 (SCAAl), cytokeratin 10, cytokeratin 6 A, trp-tRNA synthetase, and combinations thereof in a cell or tissue sample and comparing the levels of the one or more biomarkers for HPV-induced cancer in the cell or tissue sample to a control or reference level.
  • Levels of PA28 ⁇ , DJ-I protein, actin, Cl ' intracellular channel I 5 cytokeratin 8, creatine kinase B, PA28 ⁇ in the cell or tissue sample that are higher than levels in noncancer cells indicates the presence of virally transformed cells.
  • Levels of cornulin, transthyretin, HSPBl , transferrin, Hsp ⁇ 6 (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, cytokeratin 13, GST ⁇ , and cytokeratin 10 in the cell or tissue sample that are lower than levels in noncancer cells is indicative of virally transformed cells.
  • HPV-induced cancers include, but are not limited to cancer of the cervix, rectum, larynx, orthopharynx, nasopharynx, mouth, head and neck.
  • One embodiment provides a method for distinguishing invasive cervical cancer cells, premalignant cervical cells, and noncancer cervical cells by determining the levels of one or more biomarkers for cervical cancer selected from the group consisting of cornulin, PA28 ⁇ , DJ-I, actin, transthyretin, HSPBl, Cr intracellular channel 1, cytokeratin 8, transferrin, Hsp ⁇ (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, creatine kinase B, cytokeratin 13, GST ⁇ , PA28 ⁇ , Manganese SOD, lamin A/C, serpin Bl (elastase inhibitor), serpin B3 (SCAAl), cytokeratin 10, cytokeratin 6A, trp- tRNA synthetase
  • the method also includes identifying invasive cervical cancer cells, premalignant cervical cells, and noncancer cervical cells based on the levels of the one or more biomarkers detected in the cells.
  • the method optionally includes reporting the presence or absence of invasive cervical cancer cells in the cervical cell or cervical tissue sample.
  • the levels of the one or more biomarkers are detected using mass spectometry or immunocytochemistry.
  • levels of cornulin, transthyretin, HSPB 1 , transferrin, Hsp ⁇ 6 (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, cytokeratin 13, GST ⁇ , and cytokeratin 10 in the cell or cervical tissue sample are lower than levels in noncancer ceils, invasive cervical cancer cells are indicated.
  • Another embodiment provides a method for monitoring the effects of a drug in the treatment of HPV-induced cancer by determining the levels of one or more biomarkers for HPV-induced cancer selected from the group consisting of cornulin, PA28 ⁇ , DJ-I, actin, transthyretin, HSPBl, Cl * intracellular channel 1, cytokeratin 8, transferrin, Hsp ⁇ 6 (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, creatine kinase B, cytokeratin 13, GST ⁇ , PA28 ⁇ , Manganese SOD, lamin A/C, serpin Bl (elastase inhibitor), serpin B3 (SCAAl), cytokeratin 10, cytokeratin 6 A, trp-tRNA synthetase, and combinations thereof in a cell or tissue sample from subject before and after treatment with the drug and identifying changes in levels of the one or more biomarkers in the cervical cell or cervical tissue sample after treatment with the drug relative to before treatment of the
  • Still another embodiment provides a method for selecting lead compounds for drug development for the treatment of HPV-induced cancer by contacting a test compound with one or more biomarkers for HPV- induced cancer selected from the group consisting of cornulin, PA28 ⁇ , DJ-I, actin, transthyretin, HSPBl, Cl " intracellular channel 1, cytokeratin 8, transferrin, Hsp ⁇ 6 (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, creatine kinase B, cytokeratin 13, GST ⁇ , PA28 ⁇ , Manganese SOD, lamin AJC, serpin Bl (elastase inhibitor), serpin B 3 (SCAAl), cytokeratin 10, cytokeratin 6 A, and trp-tRNA synthetase assaying for binding of the test compound to one or more of the biomarkers.
  • the method also includes selecting the test compound that binds to one or more of the biomarkers for HPV-induced cancer for drug
  • One embodiment provides a method for determining the status of HPV-induced cancer, for example cervical cancer by obtaining a sample of cervical tissue from a subject and quantifying levels of cornulin in the sample of cervical tissue. Decreased levels of cornulin in the sample of cervical tissue relative to levels of cornulin in noncancer cells is indicative of invasive cervical cancer cells.
  • Still another embodiment provides a method for distinguishing premalignant cells from invasive cancer cells by obtaining a sample of tissue from a subject and quantifying levels of trp-tRNA synthetase in the sample of tissue, wherein elevated levels of trp-tRNA synthetase in the sample of tissue relative to a reference level of trp-tRNA in premalignant cells is indicative of invasive cancer cells.
  • Figure IA is a schematic diagram of the experimental design to identify biomarkers that correlate with progression to neoplasia in cervical cancer.
  • Figure IB is a schematic diagram of an exemplary analytical workflow to identify biomarkers that correlate with progression to neoplasia in cervical cancer.
  • Figures 2A-D are graphical representations of the abundance of cornulin, PA28 ⁇ , HSPBl, and MnSOD respectively in normal, HSIL, and cancer samples. Relative abundance values (Y axis) is expressed on a logarithmic scale, with each unit increment representing a 2-fold change. Each circle indicates an individual tissue sample. Patient-matched samples are connected by the dashed lines.
  • Figures 3A-D are graphical representations of immunological staining of frozen sections from patients in normal, HSIL, and cancer groups stained with A., anti-cornulin, B., anti-PA28 ⁇ , C 5 anti-Hsp27 (HSPBl), and D., anti-manganese superoxide dismutase. Each panel represent results of scoring on a standard 0-3 scale.
  • Figures 4A and B are histograms of staining intensity of commercial tissue micro array with samples drawn from an independent patient cohort. Scoring was on a standard 0-3 scale.
  • Figure 5 A is a histogram showing the coefficient of variation (percent) versus number of spots for normal cervix and cancer for total features.
  • Figure 5B is a histogram showing the coefficient of variation (percent) versus number of spots for normal cervix and cancer for differentially expressed features.
  • Figure 6 Graphs display the relative abundance of 31 proteins that were selected for mass spectrometry analysis. Relative abundance values (Y axis) are expressed on a logarithmic scale, with each unit increment representing a 2-fold change. Each circle indicates an individual tissue sample, Patient-matched samples are connected by dashed lines. Brackets indicate intergroup comparisons that met the criteria for candidate biomarkers DETAILED DESCRIPTION OF THE INVENTION I. Definitions
  • biomarker refers to an organic biomolecule which is differentially present in a sample taken from a subject of one phenotypic status (e.g., having a disease) as compared with another phenotypic status (e.g., not having the disease) or uninvolved normal tissue from the same individual.
  • a biomarker is differentially present between different phenotypic statuses if the mean or median expression level of the biomarker in the different groups is calculated to be statistically significant. Common tests for statistical significance include, among others, t-test, ANOVA,
  • Biomarkers alone or in combination, provide measures of relative risk that a subject belongs to one phenotypic status or another. Therefore, they are useful as markers for disease (diagnostics), therapeutic effectiveness of a drug (theranostics) and drug toxicity.
  • Preferred biomarkers are proteins.
  • the terms “individual”, “host”, “subject”, and “patient” are used interchangeably herein, and refer to a mammal, including, but not limited to, humans, rodents, such as mice and rats, and other laboratory animals.
  • the term “effective amount” or “therapeutically effective amount” means a dosage sufficient to treat, inhibit, or alleviate one or more symptoms of a disease state being treated or to otherwise provide a desired pharmacologic and/or physiologic effect. The precise dosage will vary according to a variety of factors such as subject-dependent variables (e.g., age, immune system health, etc.), the disease, and the treatment being administered.
  • drug refers to small molecules, protein therapeutics, vaccines, and immunomodulators. II. Biomarkers for HPV-induced Cancer
  • Biomarkers that correlate with progression to neoplasia in HPV- induced cancer have been identified. These biomarkers can be used to diagnosis or assist in the diagnosis of HPV-induced cancers such as cancer of the cervix, rectum, larynx, orthopharynx, nasopharynx, mouth, head and neck. They can also be used to increase the positive predictive value of current screening modalities, In addition, they can provide insights into the biology of HPV-induced cancer and thus provide leads for the development of nonsurgical therapies. To identify biomarkers, proteomic patterns were analyzed from samples representing normal, premalignant, and cancer tissue.
  • biomarkers include comulin, PA28 ⁇ , DJ-I, actin, transthyretin, HSPB I, CI " intracellular channel I 5 cytokeratin 8, transferrin, Hsp ⁇ (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, creatine kinase B, cytokeratin 13 GST ⁇ , PA28 ⁇ , Manganese SOD, Iamin AJC, serpin Bl (elastase inhibitor), serpin B3 (SCAAl), cytokeratin 10, cytokeratin 6A, and trp-tRNA synthetase.
  • cervical cancer Twelve have been seen before in HSIL or cancer, and results are generally concordant with the prior literature. Eleven proteins are that have not previously been linked to HPV-induced cancers, for example cervical cancer include cornulin, DJ-I, PA28 ⁇ , and PA28 ⁇ , trp-tRNA synthetase, HSP ⁇ 6, creatine kinase B, aflatoxin reductase, GST ⁇ , transthyretin, transferrin, and ⁇ 2-type 1 collagen.
  • Initial (technical) validation was performed by randomly sampling a small number of specimens from the original cohort.
  • Results agreed with the 2D-DIGE (Difference Gel Electrophoresis) analysis, lending confidence in the technical quality of the 2D-DIGE and mass spectroscopy (MS) data.
  • 2D-DIGE Difference Gel Electrophoresis
  • MS mass spectroscopy
  • the disclosed biomarkers for cervical cancer are biomolecules, preferably proteins.
  • One embodiment provides these biomolecules in isolated form.
  • the preferred biological source for detection of the biomarkers is cervical tissue including biopsy material from the cervix.
  • the biomarkers can be isolated from biological fluids, cervical secretions, exfoliated cervical cells, cervical tissue, HPV-infected cells or HPV-infected tissue, urine, blood, and serum.
  • the biomarkers can be isolated by any method known in the art, based on both their mass and their binding characteristics.
  • a sample containing the biomolecules can be subject to laser capture microdissection (LCM) and 2D- difference gel electrophoresis as described herein.
  • Other isolation techniques include chromatographic fractionation subject to further separation by, e.g., acrylamide gel electrophoresis. Knowledge of the identity of the biomarker also allows their isolation by immunoaffinity chromatography.
  • LCM laser capture microdissection
  • 2D- difference gel electrophoresis as described here
  • the disclosed biomarkers for cervical cancer can be detected by any suitable method.
  • Detection paradigms that can be employed include optical methods, electrochemical methods (voltammetry and amperometry techniques), atomic force microscopy, and radio frequency methods, e.g., multipolar resonance spectroscopy.
  • Biochips generally include solid substrates and have a generally planar surface, to which a capture reagent (also called an adsorbent or affinity reagent) is attached. Frequently, the surface of a biochip includes a plurality of addressable locations, each of which has the capture reagent bound there.
  • a capture reagent also called an adsorbent or affinity reagent
  • Protein biochips are biochips adapted for the capture of polypeptides. Many protein biochips are described in the art. These include; for example, protein biochips produced by Ciphergen Biosystems, Inc.
  • the biomarkers are detected by mass spectrometry, a method that employs a mass spectrometer to detect gas phase ions.
  • mass spectrometers are time-of-fiight, magnetic sector, quadrupole filter, ion trap, ion cyclotron resonance, electrostatic sector analyzer and hybrids of these.
  • the mass spectrometer is a laser desorption/ionization mass spectrometer.
  • the analytes are placed on the surface of a mass spectrometry probe, a device adapted to engage a probe interface of the mass spectrometer and to present an analyte to ionizing energy for ionization and introduction into a mass spectrometer.
  • a laser desorption mass spectrometer employs laser energy, typically from an ultraviolet laser, but also from an infrared laser, to desorb analytes from a surface, to volatilize and ionize them and make them available to the ion optics of the mass spectrometer.
  • a preferred mass spectrometry method following trypsin digestion, extracted peptides are spotted onto a 192-well MALDI-TOF target plate for the Applied Biosystems Incorporated (ABI) 4700 Proteomics Analyzer. Automated MALDI-TOF mass spectrometry provides a peptide mass fingerprint.
  • peptides (excluding trypsin peaks) can be subjected to collision-induced dissociation to obtain sequence information. Spectra are searched using the GPS Explorer (ABI) search tool and Mascot algorithm (Matrix Biosciences) against the NCBInr protein database.
  • the biomarkers can be first captured on a chromatographic resin having chromatographic properties that bind the biomarkers.
  • this could include a variety of methods. For example, one could capture the biomarkers on a cation exchange resin, such as CM Ceramic HyperD F resin, wash the resin, elute the biomarkers and detect by MALDI.
  • this method could be preceded by fractionating the sample on an anion exchange resin before application to the cation exchange resin.
  • one could fractionate on an anion exchange resin and detect by MALDI directly.
  • SELDI SELDI
  • an immuno-chromatographic resin that comprises antibodies that bind the biomarkers
  • wash the resin to remove unbound material
  • elute the biomarkers from the resin and detect the eluted biomarkers by MALDI or by SELDI.
  • SELDI SELDI
  • Another mass spectrometric technique for detecting the disclosed biomarkers is "Surface Enhanced Laser Description and Ionization" or "SELDL”. This refers to a method of desorption/ ⁇ onization gas phase ion spectrometry (e.g., mass spectrometry) in which an analyte (here, one or more of the biomarkers) is captured on the surface of a SELDI mass spectrometry probe.
  • an analyte here, one or more of the biomarkers
  • SELDI mass spectrometry probe There are several versions of SELDI.
  • SELDI affinity capture mass spectrometry
  • SEAC Surface-Enhanced Affinity Capture
  • This version involves the use of probes that have a material on the probe surface that captures analytes through a non-covalent affinity interaction (adsorption) between the material and the analyte.
  • the material is variously called an “adsorbent,” a “capture reagent,” an “affinity reagent” or a “binding moiety.”
  • Such probes can be referred to as “affinity capture probes” and as having an “adsorbent surface.”
  • the capture reagent can be any material capable of binding an analyte.
  • the capture reagent may be attached directly to the substrate of the selective surface, or the substrate may have a reactive surface that carries a reactive moiety that is capable of binding the capture reagent, e.g., through a reaction forming a covalent or coordinate covalent bond.
  • Epoxide and carbodiimidizole are useful reactive moieties to covalently bind polypeptide capture reagents such as antibodies or cellular receptors.
  • Nitriloacetic acid and iminodiacetic acid are useful reactive moieties that function as chelating agents to bind metal ions that interact non-covalently with histidine containing peptides.
  • Adsorbents are generally classified as chromatographic adsorbents and biospecific adsorbents.
  • Chromatographic adsorbent refers to an adsorbent material typically used in chromatography. Chromatographic adsorbents include, for example, ion exchange materials, metal chelators (e.g., nitriloacetic acid or iminodiacetic acid), immobilized metal chelates, hydrophobic interaction adsorbents, hydrophilic interaction adsorbents, dyes, simple biomolecules (e.g., nucleotides, amino acids, simple sugars and fatty acids) and mixed mode adsorbents (e.g., hydrophobic attraction/electrostatic repulsion adsorbents).
  • metal chelators e.g., nitriloacetic acid or iminodiacetic acid
  • immobilized metal chelates e.g., immobilized metal chelates
  • hydrophobic interaction adsorbents e.g., hydrophilic interaction adsorbents
  • dyes e.g.
  • Biospecific adsorbent refers to an adsorbent including a biomolecule, e.g., a nucleic acid molecule (e.g., an aptamer), a polypeptide, a polysaccharide, a lipid, a steroid or a conjugate of these (e.g., a glycoprotein, a lipoprotein, a glycolipid, a nucleic acid (e.g., DNA)-protein conjugate).
  • the biospecific adsorbent can be a macromolecular structure such as a multiprotein complex, a biological membrane or a virus. Examples of biospecific adsorbents are antibodies, receptor proteins and nucleic acids.
  • Biospecific adsorbents typically have higher specificity for a target analyte than chromatographic adsorbents.
  • a “bioselective adsorbent” refers Io an adsorbent that binds to an analyte with an affinity of at least 10 "8 M.
  • Ciphergen Bio systems, Inc. include surfaces having chromatographic or biospecific adsorbents attached thereto at addressable locations.
  • Ciphergen ProteinChip® arrays include NP20 (hydrophilic); H4 and H50 (hydrophobic); SAX-2, Q-IO and LSAX-30 (anion exchange); WCX-2, CM-IO and LWCX-30 (cation exchange); IMAC-3, lMAC-30 and IMAC 40 (metal chelate); and PS-IO, PS-20 (reactive surface with carboiraidizole, expoxide) and PG-20 (protein G coupled through carboimidizole).
  • Hydrophobic ProteinChip arrays have isopropyl or nonylphenoxy-poly(ethylene glycol)methacrylaate functionalities.
  • Anion exchange ProteinChip arrays have quaternary ammonium functionalities.
  • Cation exchange ProteinChip arrays have carboxylate functionalities.
  • Immobilized metal chelate ProteinChip arrays have have nitriloacetic acid functionalities that adsorb transition metal ions, such as copper, nickel, zinc, and gallium, by chelation,
  • Preactivated ProteinChip arrays have carboimidizole or epoxide functional groups that can react with groups on proteins for covalent binding.
  • a probe with an adsorbent surface is contacted with the sample for a period of time sufficient to allow biomarker or Momarkers that may be present in the sample to bind to the adsorbent.
  • the substrate is washed Io remove unbound material. Any suitable washing solutions can be used; preferably, aqueous solutions are employed.
  • the extent to which molecules remain bound can be manipulated by adjusting the stringency of the wash. The elution characteristics of a wash solution can depend, for example, on pH, ionic strength, hydrophobicity, degree of chaotropisra, detergent strength, and temperature. Unless the probe has both SEAC and SEND properties, an energy absorbing molecule then is applied to the substrate with the bound biomarkers.
  • the biomarkers bound to the substrates are detected in a gas phase ion spectrometer such as a ⁇ ime-of-flight mass spectrometer.
  • the biomarkers are ionized by an ionization source such as a laser, the generated ions are collected by an ion optic assembly, and then a mass analyzer disperses and analyzes the passing ions.
  • the detector then translates information of the detected ions into mass-to-charge ratios. Detection of a biomarker typically will involve detection of signal intensity. Thus, both the quantity and mass of the biomarker can be determined.
  • SELDI Surface-Enhanced Neat Desorption
  • SEND probe Another version of SELDI is Surface-Enhanced Neat Desorption (SEND), which involves the use of probes comprising energy absorbing molecules that are chemically bound to the probe surface ("SEND probe").
  • EAM energy absorbing molecules
  • EAM denotes molecules that are capable of absorbing energy from a laser desorption/ionization source and, thereafter, contribute to desorption and ionization of analyte molecules in contact therewith.
  • the EAM category includes molecules used in MALDI, frequently referred to as "matrix,” and is exemplified by cinnamic acid derivatives, sinapinic acid (SPA), cyano-hydroxy-cinnamic acid (CHCA) and dihydroxyhenzoic acid, ferulic acid, and hydroxy aceto-phenone derivatives.
  • the energy absorbing molecule is incorporated into a linear or cross-linked polymer, e.g., a polymethacrylate.
  • the composition can be a co-polymer of .alpha.-cyano-4- methacryloyloxycinnamic acid and acrylate.
  • the composition is a co-polymer of .alpha.-cyano-4-methacryloyloxycinnamic acid, acrylate and 3-(tri-ethoxy)silyl propyl methacrylate.
  • the composition is a co-polymer of .alpha.-cyano-4- methacryloyloxycinnamic acid and octadecylmethacrylate ("C 18 SEND").
  • SEAC/SEND is a version of SELDI in which both a capture reagent and an energy absorbing molecule are attached to the sample presenting surface.
  • SEAC/SEND probes therefore allow the capture of analytes through affinity capture and ionization/desorption without the need to apply external matrix.
  • the Cl 8 SEND biochip is a version of SEAC/SEND, comprising a Cl 8 moiety which functions as a capture reagent, and a CHCA moiety which functions as an energy absorbing moiety.
  • Another version of SELDI called Surface-Enhanced Photolabile
  • SEPAR Attachment and Release
  • the biological sample to be tested e.g., cervical tissue, serum or urine
  • pre-fractionation e.g., SELDI analysis.
  • a preferred method of pre-fractionation involves contacting the sample with an anion exchange chromatographic material, such as Q HyperD (BioSepra, SA).
  • Q HyperD BioSepra, SA
  • the bound materials are then subject to stepwise pH elution using buffers at pH 9, pH 7, pH 5 and pH 4.
  • Various fractions containing the biomarker are collected.
  • the sample to be tested (preferably pre-fractionated) is then contacted with an affinity capture probe comprising an cation exchange adsorbent (preferably a WCX ProteinChip array (Ciphergen Biosystems, Inc.)) or an IMAC adsorbent (preferably an IMAC3 ProteinChip array (Ciphergen Biosystems, Inc.)).
  • an affinity capture probe comprising an cation exchange adsorbent (preferably a WCX ProteinChip array (Ciphergen Biosystems, Inc.)) or an IMAC adsorbent (preferably an IMAC3 ProteinChip array (Ciphergen Biosystems, Inc.)).
  • an affinity capture probe comprising an cation exchange adsorbent (preferably a WCX ProteinChip array (Ciphergen Biosystems, Inc.)) or an IMAC adsorbent (preferably an IMAC3 ProteinChip array (Ciphergen Biosystems, Inc.)).
  • the probe is washed with a
  • a probe such as a pre- activated PSlO or PS20 ProteinChip array (Ciphergen Biosystems, Inc.). These antibodies can capture the biomarkers from a sample onto the probe surface. Then the biomarkers can be detected by, e.g., laser desorption/ionization mass spectrometry. c. Other Techniques
  • Mass spectrometry-based Multi-Reaction Monitoring can also be used to detect the biomarkers.
  • Mass spectrometry-based Multi-Reaction Monitoring has been described by Gerber et al., Proc Natl Acad Set USA., 100(12):6940-5 (2003). The strategy has two stages. The first involves identification of suitable tryptic peptides from a candidate biomarker. The process of identifying suitable peptides was discussed and illustrated in the Introduction (as a response to a specific reviewer concern). Standard peptides are then synthesized, corresponding to two or more of these peptides. During synthesis, a stable isotope (e.g. 13C) is inserted at a single amino acid residue.
  • a stable isotope e.g. 13C
  • the synthetic peptide is then used as standard for absolute quantification of protein present in a clinical sample.
  • Proteins are extracted from the clinical sample, digested with trypsin, and subjected to mass spectrometry in an ABI 4000 Q Trap system mass spectrometer set to detect the peptide of interest together with the non-isobaric standard peptide.
  • the ratio of normal (sample derived) and heavy (synthetic) peptide will be monitored.
  • An advantage to the method is that the sample can be spiked with many peptides simultaneously, permitting multiple monitoring of different species. d. Data Analysis
  • Time-of-flight mass spectrometry generates a time-of-flight spectrum.
  • the time-of-flight spectrum ultimately analyzed typically does not represent the signal from a single pulse of ionizing energy against a sample, but rather the sum of signals from a number of pulses. This reduces noise and increases dynamic range.
  • This time-of-flight data is then subject to data processing.
  • data processing typically includes TOF-to-M/Z transformation to generate a mass spectrum, baseline subtraction to eliminate instrument offsets and high frequency noise filtering to reduce high frequency noise.
  • Data generated by desorpt ⁇ on and detection of biomarkers can be analyzed with the use of a programmable digital computer.
  • the computer program analyzes the data to indicate the number of biomarkers detected, and optionally the strength of the signal and the determined molecular mass for each biomarker detected.
  • Data analysis can include steps of determining signal strength of a biomarker and removing data deviating from a predetermined statistical distribution.
  • the observed peaks can be normalized, by calculating the height of each peak relative to some reference.
  • the reference can be background noise generated by the instrument and chemicals such as the energy absorbing molecule which is set at zero in the scale.
  • the computer can transform the resulting data into various formats for display.
  • the standard spectrum can be displayed, but in one useful format only the peak height and mass information are retained from the spectrum view, yielding a cleaner image and enabling biomarkers with nearly identical molecular weights to be more easily seen.
  • two or more spectra are compared, conveniently highlighting unique biomarkers and biomarkers that are up- or down-regulated between samples. Using any of these formats, one can readily determine whether a particular biomarker is present in a sample.
  • Peak Analysis generally involves the identification of peaks in the spectrum that represent signal from an analyte. Peak selection can be done visually, but software is available, as part of Ciphergen's ProteinChip® software package, that can automate the detection of peaks. In general, this software functions by identifying signals having a signal-to-noise ratio above a selected threshold and labeling the mass of the peak at the centroid of the peak signal. In one useful application, many spectra are compared to identify identical peaks present in some selected percentage of the mass spectra. One version of this software clusters all peaks appearing in the various spectra within a defined mass range, and assigns a mass (N/Z) to all the peaks that are near the mid-point of the mass (M/Z) cluster.
  • Software used to analyze the data can include code that applies an algorithm to the analysis of the signal to determine whether the signal represents a peak in a signal that corresponds to a biomarker according to the present invention.
  • the software also can subject the data regarding observed biomarker peaks to classification tree or ANN analysis, to determine whether a biomarker peak or combination of biomarker peaks is present that indicates the status of the particular clinical parameter under examination. Analysis of the data may be "keyed" to a variety of parameters that are obtained, either directly or indirectly, from the mass spectrometric analysis of the sample.
  • the biomarkers can be measured by immunoassay.
  • Immunoassay requires biospecific capture reagents, such as antibodies, to capture the biomarkers.
  • Antibodies can be produced by methods well known in the art, e.g., by immunizing animals with the biomarkers. Biomarkers can be isolated from samples based on their binding characteristics. Alternatively, if the amino acid sequence of a polypeptide biomarker is known, the polypeptide can be synthesized and used to generate antibodies by methods well known in the art.
  • Biomarkers including, for example, sandwich immunoassays including ELISA or fluorescence-based immunoassays, as well as other enzyme immunoassays can be used for detecting the biomarkers.
  • a biospecific capture reagent for the biomarker is attached to the surface of an MS probe, such as a pre- activated ProteinChip array. The biomarker is then specifically captured on the biochip through this reagent, and the captured biomarker is detected by mass spectrometry.
  • Quantitative immunochemical techniques can also be used.
  • the Quantitative Tissue Biomarker Platform from HistoRx can be used to quantified levels of biomarkers. This platform is commercially available and quantitates protein expression within subcellular compartments in tissue sections automatically, with a high level of precision.
  • the Quantitative Tissue Biomarker Platform from HistoRx can be used to quantified levels of biomarkers. This platform is commercially available and quantitates protein expression within subcellular compartments in tissue sections automatically, with a high level of precision.
  • HPV E6 and E7 bind directly to p53, Rb, and a number of other cellular proteins (reviewed in references [10, 11]). Effects potentially attributable to direct interactions of HPV oncoproteins with these and other cellular proteins account for at least a quarter of the changes in the data provided in the Examples.
  • Serpin Bl a member of a large family of serine protease inhibitors, binds directly to E7 in a pulldown assay [32]. It is down- regulated in vitro in E7-transfected cells [33], consistent with the down- regulation observed here in HSIL. Glutathione- S -transferase similarly decreases in E7-transfected cells, although it is unknown if this reflects a direct protein-protein interaction [37].
  • Creatine kinase B and tryptophanyl tRNA synthetase are p53-repressible enzymes [34, 35] that increased significantly in cancer.
  • expression of these proteins may be influenced by factors in addition to p53 ; the direction of the changes in expression, in both cases, is consistent with HPV E6-mediated loss of p53 function.
  • HSPBl apparently falls into the same category of differentiation markers.
  • the observed decline in cancer specimens was paradoxical, in that expression of this and other HSPs have been widely observed to increase in proteomic studies of cancer cells.
  • HSPBl may have a specialized function as a cornification chaperone, and it is expressed at high levels in the upper levels of normal stratified epithelium and in in vitro differentiated keratinocytes (Fig. 4 and references [29, 39]).
  • Relatively high levels were seen in normal cervix, a slight decline in HSIL, and a marked decline in cancer, especially in some specimens.
  • a decline in expression in less-differentiated lesions plausibly reflects their inability to undergo terminal differentiation in the presence of HPV oncoproteins. Consistent with this, in the tissue microarray, the highest frequency of
  • HSPBl -negative specimens was in the least-differentiated (grade 3) tumors. It will be of interest to investigate the mechanism of heterogeneity in highgrade cancers and to determine whether HSPBl status has independent prognostic or predictive value. This will require a separate study, as clinical outcome data are not available for the subjects used here.
  • Hsp ⁇ Hsp20
  • cervical cancer Like other human cancers, cervical cancer typically develops only after a long latency period. Effects attributable to variation and selection for growth advantage are expected to occur stochastically during latency; that is, both the timing and whether a given change occurs at all will vary between patients.
  • the oncoprotein, DJ-I may fall into this category, DJ-I significantly increased in cancer versus normal tissue, whereas expression values in HSIL showed considerable dispersion.
  • DJ-I transforms mouse NIH3T3 cells in vitro and is overexpressed in many cancers including: breast, lung, pancreatic, ovarian, and prostate [40-44].
  • Mechanistic studies show that DJ-I is a negative regulator of the tumor suppressor, PTEN [45].
  • PTEN a negative prognostic indicator in cervical cancer [46, 47]
  • direct mutation or loss of heterozygosity at the PTEN locus is rare [46].
  • DJ-I could provide a mechanism for down- regulation in the absence of direct mutation or loss of the PTEN gene. It is well established that deficiency of DJ-I (also known as PARJC7) sensitizes dopaminergic neurons to stress-mediated apoptosis in hereditary Parkinson's disease(reviewed in reference [48]). Regulation of apoptosis appears to be the common HnIc explaining the role of DJ-I in these disparate diseases. Interestingly, expression of Serpin B 1 , another biomarker discovered in this study, has previously been shown to be PTEN dependent [49], Thus down- regulation of PTEN in HSIL could provide another explanation for the observed down regulation of Serpin Bl (in addition to direct interaction of HPV E7 with Serpin Bl).
  • IFN- ⁇ inducible proteins were identified as up-regulated in cancer. Unlike IFN- ⁇ and IFN- ⁇ , which are expressed by many cell types, IFN- ⁇ is expressed only by T cells and NK cells. Thus, expression of IFN- ⁇ - inducible genes in cancers cells is expected to occur only as a consequence of cell-cell interactions within the tissue microenvironment. Two of the IFN- ⁇ -inducible proteins, PA28 ⁇ and PA28 ⁇ , activate the 2OS proteasome complex, which presents antigens via the MHC I pathway. Although the up- regulation of these proteins is novel in cervical cancer, up-regulation of PA 28 ⁇ has been described previously in infiltrating ductal breast carcinoma [51].
  • IFN- ⁇ -inducible tryptophanyl protein tRNA synthetase
  • tRNA synthetase Another IFN- ⁇ -inducible tryptophanyl protein, tRNA synthetase, has been hypothesized to protect cells from tryptophan starvation following IFN- ⁇ -mediated induction of the catabolic enzyme, indoleamine 2,3 dioxygenase [52].
  • Transthyretin is a negative acute-phase serum protein that decreases in inflammatory conditions including many cancers [53]. Transferrin, another serum transporter that decreased in cancer, has been reported to decrease in ovarian cancer [54]. The decrease in extracellular matrix protein, ⁇ 2-type 1 collagen that occurred in HSIL may be an indirect effect of IFN- ⁇ , mediated via stimulation of the IRF-I transcription factor [55].
  • the biomarkers can be used in diagnostic tests to assess HPV- induced cancer status in a subject, e.g., to distinguish between normal cells, high-risk premalignant cells, and invasive carcinoma.
  • HPV- induced cancer status includes any distinguishable manifestation of the disease, including non-disease.
  • disease status includes, without limitation, the presence or absence of disease (e.g., cancer v. non- cancer), the risk of developing disease, the stage of the disease (e.g., non-invasive or early-stage cancer v. invasive or metastatic cancer), the progress of disease (e.g., progress of disease or remission of disease over time) and the effectiveness or response to treatment of disease.
  • HPV-induced cancers include, but are not limited to cancer of the cervix, rectum, larynx, orthopharynx, nasopharynx, mouth, head and neck.
  • the power of a diagnostic test to correctly predict status is commonly measured as the sensitivity of the assay, the specificity of the assay or the area under a receiver operated characteristic ("ROC") curve.
  • Sensitivity is the percentage of true positives that are predicted by a lest to be positive, while specificity is the percentage of true negatives that are predicted by a test to be negative.
  • An ROC curve provides the sensitivity of a test as a function of 1 -specificity.
  • Positive predictive value is the percentage of actual positives who test as positive.
  • Negative predictive value is the percentage of actual negatives that test as negative.
  • the biomarkers of this invention show a statistical difference in different cervical cancer statuses of at least p ⁇ 0.05, p ⁇ 10 "2 , p ⁇ 10 "3 , p ⁇ 10 "4 or p ⁇ 10 ⁇ 5 . Diagnostic tests that use these biomarkers alone or in combination show a sensitivity and specificity of at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at east 98% and about 100%.
  • Each biomarker listed in Table 1 is differentially expressed in cervical cancer, and, therefore, each is individually useful in aiding in the determination of cervical cancer status.
  • the method involves, first, measuring the selected biomarker in a subject sample using the methods described herein, e.g., capture on a MALDI biochip followed by detection by mass spectrometry and, second, comparing the measurement with a diagnostic amount or cut-off that distinguishes a positive cervical cancer status from a negative cervical cancer status.
  • the diagnostic amount represents a measured amount of a biomarker above which or below which a subject is classified as having a particular cervical cancer status. For example, if the biomarker is up-regulated compared to normal during cervical cancer, then a measured amount above the diagnostic cutoff provides a diagnosis of cervical cancer. Alternatively, if the biomarker is down-regulated during cervical cancer, then a measured amount below the diagnostic cutoff provides a diagnosis of cervical cancer.
  • the particular diagnostic cut-off used in an assay by adjusting the particular diagnostic cut-off used in an assay, one can increase sensitivity or specificity of the diagnostic assay depending on the preference of the diagnostician.
  • the particular diagnostic cut-off can be determined, for example, by measuring the amount of the biomarker in a statistically significant number of samples from subjects with the different cervical cancer statuses and drawing the cut-off to suit the diagnostician's desired levels of specificity and sensitivity.
  • cornulin levels are measured in a sample and compared to a control.
  • a representative control is cervical tissue known to be free of HPV-induced cancer from the same or a different individual.
  • a control can also be a reference standard for example a reference protein in the same sample known not to change levels.
  • Cornulin levels are significantly higher in maturing squamous cells of the normal epithelium compared to non-cancer cells, reduced in non-dysplastic cells in HSIL, and non-detectable in invasive cancer cells.
  • biomarkers that have reduced levels in invasive cancer cells relative to noncancer cells or are down- regulated in invasive cancer cells include transthyretin, HSPBl, transferrin, Hsp ⁇ (HSP20), aflatoxin reductase, ⁇ 2 type I collagen, cytokeratin 13, GST ⁇ , and cytokeratin 10.
  • One or more of the biomarkers with reduced levels in invasive cancer cells relative to noncancer cells can be used to select or identify invasive cancer cells, to distinguish invasive cancer cells from noncancer cells, or to assist in the diagnosis of HPV-induced cancer.
  • Biomarkers for HPV -induced cancer that have increased levels in invasive cancer cells relative to noncancer cells or are upregulated in invasive cancer cells relative to noncancer cells include PA28 ⁇ , DJ-I, actm, Cl " intracellular channel 1, cytokeratin 8, creatine kinase B and PA28 ⁇ .
  • One or more of the biomarkers with increased levels in invasive cancer cells relative to noncancer cells can be used to select or identify invasive cancer cells, to distinguish invasive cancer cells from noncancer cells, or to assist in the diagnosis of HPV-induced cancer.
  • Biomarkers for HPV-induced cancer that have decreased levels or are downregulated in premalignant cells relative to noncancer cells include cornulin, transthyretin, cytokeratin 13, lamin A/C ; serpin Bl (elastase inhibitor), serpin B3(SCCA1) ; cytokeratin 10, and cytokeratin 6A.
  • One or more of the biomarkers with reduced levels in premalignant cells relative to noncancer cells can be used to select or identify premalignant cells, to distinguish premalignant cells from noncancer cells, or to assist in identifying the status of HPV-induced cancer.
  • Biomarkers for HPV-induced cancer that have increase levels or are uregulated in premalignant cells relative to noncancer cells include cytokeratin 8 and Manganese SOD.
  • One or more of the biomarkers with increased levels in invasive premalignant cells relative to noncancer cells can be used to select or identify premalignant cells, to distinguish premalignant cells from noncancer cells, or to assist in identifying the status of HPV- induced cancer.
  • Biomarkers for HPV-induced cancer that have decreased levels or are downregulated in invasive cancer cells relative to premalignant cells include cornulin, PA28 ⁇ , HSPBl , transferrin, and ⁇ 2 type I collagen.
  • One or more of the biomarkers with reduced levels in invasive cells relative to premalignant cells can be used to select or identify invasive cancer cells, to distinguish premalignant cells from noncancer cells, or to assist in identifying the status of HPV-induced cancer.
  • trp-tPvNA synthetase is upregulated in invasive cancer cells relative to premaligant cells. This biomarker can be used to to distinguish premalignant cells from noncancer cells, or to assist in identifying the status of HPV- induced cancer.
  • Preferred biomarkers for HPV-induced cancer include cornulin, DJ-I, PA28 ⁇ , and PA28 ⁇ , trp-tRNA synthetase, HSP ⁇ 6, creatine kinase B, aflatoxin reductase, GST ⁇ , transthyretin, transferrin, ⁇ 2-ty ⁇ e 1 collagen, and combinations thereof.
  • biomarkers are useful diagnostic biomarkers, it has been found that a combination of biomarkers can provide greater predictive value of a particular status than single biomarkers alone. Specifically, the detection of a plurality of biomarkers in a sample can increase the sensitivity and/or specificity of the test. Thus, in one embodiment, two or more, three or more, four or more or even five or more of the biomarkers in Table 1 can be detected and used to assess the status of cervical cancer in a subject. B. Determining Risk of Developing Disease
  • Biomarker amounts or patterns are characteristic of various risk states, e.g., high, medium or low.
  • the risk of developing a disease is determined by measuring the relevant biomarker or biomarkers and then either submitting them to a classification algorithm or comparing them with a reference amount and/or pattern of biomarkers that is associated with the particular risk level.
  • Another embodiment provides methods for determining the stage of disease in a subject.
  • Each stage of the disease has a characteristic amount of a biomarker or relative amounts of a set of biomarkers (a pattern).
  • the stage of a disease is determined by measuring the relevant biomarker or biomarkers and then either submitting them to a classification algorithm or comparing them with a reference amount and/or pattern of biomarkers that is associated with the particular stage.
  • detection biomarker cornulin can be used to distinguish between early-stage (non-invasive) to invasive cervical cancer.
  • Still another embodiment provides methods for determining the course of disease in a subject.
  • Disease course refers to changes in disease status over time, including disease progression (worsening) and disease regression (improvement). Over time, the amounts or relative amounts (e.g., the pattern) of the biomarkers changes.
  • This method involves measuring one or more biomarkers in a subject at least two different time points, e.g., a first time and a second time, and comparing the change in amounts, if any. The course of disease is determined based on these comparisons. Similarly, this method is useful for determining the response to treatment. If a treatment is effective, then the biomarkers will trend toward normal, while if treatment is ineffective, the biomarkers will trend toward disease indications.
  • the methods further include managing subject treatment based on the status.
  • Such management includes the actions of the physician or clinician subsequent to determining cervical cancer status. For example, if a physician makes a diagnosis of cervical cancer, then a certain regime of treatment, such as prescription or administration of chemotherapy, radiation, immunotherapy might follow. Alternatively, a diagnosis of non-cervical cancer or benign cervical-disease might be followed with further testing to determine a specific disease that might the patient might be suffering from. Also, if the diagnostic test gives an inconclusive result on cervical cancer status, further tests may be required.
  • One embodiment provides a method for selecting a subject for treatment for cervical cancer by detecting the presence or quantity of one or more biomarkers in Table 1 in a sample from a subject suspected of having cervical cancer, comparing the levels of biomarker in the sample to a predetermined standard, wherein the patient is selected for treatment for cervical cancer if certain biomarkers or levels of biomarkers are detected in the sample.
  • Additional embodiments relate to the communication of assay results or diagnoses or both to technicians, physicians or patients, for example.
  • computers will be used to communicate assay results or diagnoses or both to interested parties, e.g.: physicians and their patients.
  • the assays will be performed or the assay results analyzed in a country or jurisdiction which differs from the country or jurisdiction to which the results or diagnoses are communicated.
  • a diagnosis based on the presence or absence in a test subject of any the biomarkers of Table 1 is communicated to the subject as soon as possible after the diagnosis is obtained.
  • the diagnosis may be communicated to the subject by the subject's treating physician.
  • the diagnosis may be sent to a test subject by email or communicated to the subject by phone.
  • a computer may be used to communicate the diagnosis by email or phone.
  • the message containing results of a diagnostic test may be generated and delivered automatically to the subject using a combination of computer hardware and software which will be familiar to artisans skilled in telecommunications.
  • all or some of the method steps, including the assaying of samples, diagnosing of diseases, and communicating of assay results or diagnoses may be carried out in diverse (e.g., foreign) jurisdictions.
  • the biomarkers can be used to screen for compounds that modulate the expression of the biomarkers in vitro or in vivo, which compounds in turn may be useful in treating or preventing cervical cancer in patients.
  • Compounds suitable for therapeutic testing may be screened initially by identifying compounds which interact with one or more biomarkers listed in Table 1.
  • screening might include recombinantly expressing a biomarker listed in Table 1 , purifying the biomarker, and affixing the biomarker to a substrate.
  • Test compounds would then be contacted with the substrate, typically in aqueous conditions, and interactions between the test compound and the biomarker are measured, for example, by measuring elution rales as a function of salt concentration.
  • Certain proteins may recognize and cleave one or more biomarkers of Table 1 , in which case the proteins may be detected by monitoring the digestion of one or more biomarkers in a standard assay, e.g., by gel electrophoresis of the proteins.
  • the ability of a test compound to inhibit the activity of one or more of the biomarkers of Table I may be measured.
  • the techniques used to measure the activity of a particular biomarker will vary desponding on the function and properties of the biomarker. For example, an enzymatic activity of a biomarker may be assayed provided that an appropriate substrate is available and provided that the concentration of the substrate or the appearance of the reaction product is readily measurable.
  • the ability of potentially therapeutic test compounds to inhibit or enhance the activity of a given biomarker may be determined by measuring the rates of catalysis in the presence or absence of the test compounds.
  • the ability of a test compound to interfere with a non- enzymatic (e.g., structural) function or activity of one of the biomarkers of Table I may also be measured.
  • the self-assembly of a multi- protein complex which includes one of the biomarkers of Table I may be monitored by spectroscopy in the presence or absence of a test compound.
  • test compounds which interfere with the ability of the biomarker to enhance transcription may be identified by measuring the levels of biomarker- dependent transcription in vivo or in vitro in the presence and absence of the test compound.
  • Test compounds capable of modulating the activity of any of the biomarkers of Table I may be administered to patients who are suffering from or are at risk of developing cervical cancer or other cancer.
  • the administration of a test compound which increases the activity of a particular biomarker may decrease the risk of cervical cancer in a patient if the activity of the particular biomarker in vivo prevents the accumulation of proteins for cervical cancer.
  • the administration of a test compound which decreases the activity of a particular biomarker may decrease the risk of cervical cancer in a patient if the increased activity of the biomarker is responsible, at least in part, for the onset of cervical cancer.
  • screening a test compound includes obtaining samples from test subjects before and after the subjects have been exposed to a test compound.
  • the levels in the samples of one or more of the biomarkers listed in Table 1 may be measured and analyzed to determine whether the levels of the biomarkers change after exposure to a test compound.
  • the samples may be analyzed by mass spectrometry, as described herein, or the samples may be analyzed by any appropriate means known to one of skill in the art.
  • the levels of one or more of the biomarkers listed in Table 1 may be measured directly by Western blot using radio- or fluorescently-labeled antibodies which specifically bind to the biomarkers.
  • changes in the levels of mRNA encoding the one or more biomarkers may be measured and correlated with the administration of a given test compound to a subject.
  • the changes in the level of expression of one or more of the biomarkers may be measured using in vitro methods and materials.
  • human tissue cultured cells which express, or are capable of expressing, one or more of the biomarkers of Table 1 may be contacted with test compounds.
  • Subjects who have been treated with test compounds will be routinely examined for any physiological effects which may result from the treatment.
  • the test compounds will be evaluated for their ability to decrease disease likelihood in a subject.
  • test compounds will be screened for their ability to slow or stop the progression of the disease.
  • Disease course refers to changes in disease status over time, including disease progression (worsening) and disease regression (improvement).
  • the amounts or relative amounts (e.g., the pattern) of the biomarkers changes.
  • biomarkers comulin, transthyretin, and HSPBl are decreased in disease. Therefore, the trend of these markers, either increased or decreased over time toward diseased or non-diseased indicates the course of the disease.
  • this method involves measuring one or more biomarkers in a subject at least two different time points, e.g., a first time and a second time, and comparing the change in amounts, if any.
  • the course of disease is determined based on these comparisons. Similarly, this method is useful for determining the response to treatment. If a treatment is effective, then the biomarkers will trend toward normal, while if treatment is ineffective, the biomarkers will trend toward disease indications.
  • kits An exemplary kit includes a solid substrate having a hydrophobic function, such as a protein biochip (e.g., a Ciphergen H50 ProteinChip array, e.g., ProteinChip array) and a sodium acetate buffer for washing the substrate, as well as instructions providing a protocol to measure the biomarkers on the chip and to use these measurements to diagnose HPV- induced cancer or the progression of HPV-induced cancer.
  • a protein biochip e.g., a Ciphergen H50 ProteinChip array, e.g., ProteinChip array
  • a sodium acetate buffer for washing the substrate
  • instructions providing a protocol to measure the biomarkers on the chip and to use these measurements to diagnose HPV- induced cancer or the progression of HPV-induced cancer.
  • Specimens were obtained from the Institute Nacional de Enfermedades Neoplasicas (INEN, Li ma, Peru). Patients who had positive Pap smears and were scheduled to undergo gynecologic surgery were eligible. Following institutional review board guidelines, subjects were asked to provide informed consent for use of their tissue in research. Patients with a finding of HSIL contributed both lesional tissue and normal tissue from elsewhere in the cervix. Patients with a finding of invasive cancer contributed lesional tissue only (typically, no normal anatomy remained). Three comparisons were made: (1) cancer vs. normal (unpaired), (2) HSIL vs. normal (paired), and (3) cancer vs. HSIL (unpaired).
  • Tissues were snap frozen, and epithelial or lesional tissue was later collected by LCM as described [23].
  • An invariant internal standard was prepared as a mixture of normal cervical tissue from a patient who underwent transabdominal hysterectomy for symptomatic leiomyomas and cervical squamous cell carcinoma from a different patient who underwent radical hysterectomy.
  • Frozen sections (5 ⁇ m) were stained briefly with Nuclear Fast Red and LCM was performed using an Arcturus PixCell He microscope. Caps, with polymer film and adherent cells, were placed onto a microcentrifuge tube containing lysis buffer (7 M urea, 2 M thiourea, 4% CHAPS, 0.4 mM AEBSF (protease inhibitor), 40 mM Tris-HCl pH 8, 5 mM Mg(OAc)2). Tubes were inverted to wet the polymer film and incubated for 30 min at room temperature. The resulting extracts were sonicated five times for 30 sec each and centrifuged at 14,000 g for 15 min, and the supernatant was transferred to a fresh tube.
  • lysis buffer 7 M urea, 2 M thiourea, 4% CHAPS, 0.4 mM AEBSF (protease inhibitor), 40 mM Tris-HCl pH 8, 5 mM Mg(OAc)2. Tubes were inverted to wet the
  • Quantities of labeling reagents were based on the estimate that 5000 cell samples contained about 1 ⁇ g of extractable protein.
  • Tris-(2-carboxyethyl)-phosphine (TCEP) was added (0.4 nmol), and the mixture was incubated 1 h at 37° C.
  • Cy5 sulfhydryl-reactive dye was added (0.8 nmol, GE Healthcare, Buckinghamshire, UK) and incubation was continued for 30 min at 37° C.
  • the reaction was terminated by addition of an equal volume of 2X sample buffer (7 M urea, 2 M thiourea, 4% CHAPS, 130 mM dithiothreitol, 2% ampholytes).
  • the sample was diluted to a final volume of 450 ⁇ l with rehydration buffer (7 M urea, 2 M thiourea, 4% CHAPS, 13 mM dithiothreitol, 1% ampholytes).
  • rehydration buffer 7 M urea, 2 M thiourea, 4% CHAPS, 13 mM dithiothreitol, 1% ampholytes.
  • the samples were stored frozen at -80 0 C until use. Although freezing and thawing of samples reduced the quality of 2D gels in our previous study, saturation labeling prior to freezing protects against this effect, perhaps by blocking oxidation of free cysteines.
  • the internal standard was prepared by grinding bulk tissue under liquid nitrogen. Proteins were solubilized as described for LCM samples. Protein concentration was measured, and the samples were saturation-labeled with Cy3 using the same ratio of dye and TCEP to protein as for the LCM samples.
  • a mixture of Cy5-labeled sample and Cy3 -labeled internal standard was loaded into a 24 cm strip holder containing a pH 3-10 nonlinear IPG strip and overlaid with Immobiline DryStrip Cover Fluid (GE Healthcare). Rehydration was carried out for 15 h at 20° C with an applied electric field of 30 V. For first-dimension electrophoresis, electric potentials of 500 V for 1 h, 1000 V for 2 h, and 8000 V for 7 h were applied. The strip was removed and equilibrated twice in 6 M urea, 100 mM Tris-HCl pH 8, 2% SDS, 32.5 mM dithiothreitol, and 30% glycerol for 15 min at room temperature.
  • the strip was applied to the top of a 12.5% SDS gel (25 cm X 20 cm X 0.1 cm), and electrophoresis was performed using 10 mA per gel overnight.
  • the gel was removed and scanned using a GE Healthcare Typhoon 9400 Series Variable Imager.
  • Preparative Gel for Protein Identification For the preparative gel, a volume of cervical tissue protein lysate containing 500 ⁇ g of internal standard in lysis buffer was labeled in a reaction containing 20 mM Cy3 sulfhydryl-reactive dye, IX sample buffer (7 M urea, 2 M thiourea, 4% CHAPS), 1% Pharmalytes, and 130 mM dithiothreitol in a final volume of 450 ⁇ l. The mixture was loaded into a 24 cm strip holder containing a pH 3-10 nonlinear IPG strip and overlaid with Immobiline DryStrip Cover Fluid. The sample was separated in the first and second dimensions as described above.
  • the gel was scanned, and then fixed with 30% methanol and 7.5 % acetic acid solution.
  • the preparative gel image was matched to the analytical gel images to obtain coordinates for spots of interest. Protein plugs were robotically cored and transferred to a 96 well plate for tryptic digestion.
  • Each microarray contained 30 carcinoma specimens, 10 CIN specimens, 10 inflamed cervical tissue specimens, and 10 normal specimens. Slides were deparaffinized and run through graded alcohols to distilled water. Slides were prelreated with Target Retrieval Solution PH 6.0, (Dako Corp, Carpinteria, CA.) using a steamer (Black and Decker rice steamer) and rinsed in distilled water. Antibody staining and development were the same as for the frozen sections. Results
  • HSIL samples demonstrated >90% involvement of the epithelium with high-grade dysplastic cells that had not invaded through the basement membrane.
  • Cervical cancer samples demonstrated moderately differentiated, nonkeratinizing squamous cell carcinomas. All preparative sections were stained with Nuclear Fast Red for LCM. The more intensely stained epithelial or lesional tissue was collected, leaving behind the lighter-stained stroma.
  • Tissue biomarkers with changes of ⁇ 2.0-fold might be difficult to measure reliably in a clinical laboratory (e.g., by immunohistochemistry) and thus would be unlikely to be widely adopted.
  • Application of a filter based on fold change has been shown to further reduce FDR [28].
  • 53 features (spots) were identified as candidate biomarkers.
  • Example 2 Proteomic patterns in normal, HSIL, and cancer Based on the SAM analysis, there were 42 spots that distinguished cancer from normal, 23 that distinguished HSIL from normal, and 9 that distinguished cancer from HSIL. Some spots were significant in two or more of these pairwise comparisons (20/53) and one distinguished all three sample groups. Individual data values for four representative markers are presented in Fig 3A-D.
  • the vertical axis represents the "internal ratio" (IR) of expression for each spot relative to the internal standard in the same gel Data are plotted as Iog2 IR, such that each unit on the vertical axis corresponds to a 2-fold change. Dashed lines, which connect paired normal and HSIL specimens from the same patient, illustrate how the availability of paired samples reveal consistent expression trends that might not otherwise have been apparent. Viewing group means, in addition to the individual values, provides additional insight. HSIL has its own, distinctive, pattern of expression, with some markers more cancer-like, and others more normal- like.
  • Example 3 Match to preparative gel and mass spectrometry analysis To identify spots at the molecular level, a separate preparative gel was run with 500 ⁇ g of Cy3 -labeled mixed internal standard, matched the spot map to the master map from the analytical gels, picked spots of interest, and obtained mass spectrometry identifications as described in Example 1, 31 spots were picked including only those that could be unambiguously matched between the preparative gel and the master map and that were well resolved from abundant neighboring spots, and obtained definite identifications for 29. Among these, there were five instances where nearby, co-regulated spots proved to be the same protein, leaving the 23 unique proteins listed in Table 1.
  • Example 5 Validation by immunohistochemical staining
  • three specimens from each group in the original cohort were randomly selected and immunohistochemistry was performed on them.
  • Four markers were investigated because of the commercial availability of antibodies suitable for immunochemistry and because the markers were (a) novel in the context of cervical cancer or (b) there was a discrepancy between the data and previous reports.
  • Serial sections were stained with antibodies to cornulin, PA28 ⁇ , HSPBl and MnSOD and the slides were scored on a standard scale of 0 to 3 based on intensity of staining (Figs. 3A- D). Results showed generally good agreement with the 2D-DIGE quantification (compare Figs. 2A-D with Figs.
  • Prominent cornulin staining is evident in the maturing squamous cells of the normal epithelium, in only a thin rim of non-dysplastic cells representing the outermost layer of epithelium in HSIL, and not at all in an invasive cancer sample. PA28 ⁇ staining was evident only in cancer, and not in normal or HSIL.
  • HSPBl staining was similar to cornulin, with intense staining in the normal epithelium, consistent with reports that this small heat shock protein is a cornification chaperone [29, 30], HSPBl staining was also present, but at a lower level in HSIL and cancer (panel C), consistent with a prior immunohistochemical study of HSPBl expression in cervical pre-cancerous lesions and cancer [31 j. There was HSPBl staining in areas of necrosis in cancer samples (not shown) but necrotic areas were excluded in the LCM procedure and thus not represented in the 2D-DIGE sampling.
  • Immunohistochemical staining of MnSOD showed expression in a thin layer of cells along the basal layer of the normal squamous epithelium, an increase in expression in HSIL, and somewhat of a decline in cancer, again consistent with 2D-DIGE.
  • additional immunohistochemistry experiments were performed using formalin fixed paraffin embedded tissue microa ⁇ xays (Figs. 4A-B).
  • Tissue microarrays were stained with anti- cornulin or anti-Hsp27 (HSPBl), Staining intensity was scored on the same 0 to 3 scale.
  • Statistical analysis was performed by one-way ANOVA. Differences contributing to group variance were calculated in pair-wise comparisons using the Tukey's Honestly Significant Difference Test. Anti-comulin staining (Fig. 4A) showed no apparent difference between normal and inflamed tissue, but a highly significant difference between these two groups and cancer (pO.001).
  • the CIN samples had a wide distribution of values centered in between normal and cancer. The variance was attributed to the presence of multiple grades of CIN in this cohort. Because of the wi thin-group variance, comparisons of CIN to the other groups did not reveal a statistically significant difference.
  • Example 6 Reproducibility of combined LCM and 2D-D ⁇ GE analysis
  • Specimens A and B consisted of a normal epithelium and a malignancy from human cervix. Each specimen was sampled in triplicate by LCM and analyzed proteins by 2DDIGE. A pooled internal standard prepared by macroscopic dissection of tissue blocks representing the two specimens was used. Protein spots based on their presence in all six internal standard images were matched, 261 spots across the entire data set were matched. For each spot in each gel, the abundance relative to the same feature in the internal standard was determined to derive an "internal ratio" (IR).
  • IR internal ratio
  • IR was determined as well as a within-group coefficient of variation (CV).
  • CV within-group coefficient of variation
  • a histogram showing the distribution of CVs is shown in Fig. 5.
  • the median CVs for Specimens A (normal cervical epithelium) and B (squamous cervical carcinoma) were 23.1 % and 22.7%, respectively.
  • Spots were ranked in order of decreasing absolute value of d score as determined by SAM algorithm. Dark grey shading denotes up-regulation in the indicated comparison, light grey shading denotes down-regulation, lack of shading denotes not significant. Spot numbers are as they appear on the master analytical gel. Protein accession numbers are from the SwissProt database. Predicted protein masses and isoelectric points are based on conceptual translation, CN: comparison of cancer and normal. HN: comparison of HSEL and normal CH: comparison of cancer and HSIL. b) Number of peptides that matched the identified protein sequence, followed by percent sequence coverage. c) Mascot score based on combined peptide mass fingerprinting and masses of collisionally-induced dissociation peptides d) Fold change in expression. Values in parentheses are decreases, other values are increases. e) Absolute value of d(i) from SAM calculation, f) False discovery rate from SAM calculation.
  • pl6INK4A immunohistochemistry is superior to HPV in situ hybridization for the detection of highrisk
  • DJ-I a negative regulator of PTEN

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Abstract

Cette invention concerne des marqueurs biologiques qui ont été identifiés et se corrèlent à l'évolution de la néoplasie dans le cancer induit par le virus du papillome humain (HPV), par exemple, le cancer du col de l'utérus. Ces marqueurs biologiques peuvent être utilisés pour dépister ou contribuer au dépistage d'un cancer induit par le HPV. Ils peuvent également être utilisés pour accroître la valeur prédictive positive des modalités de criblage actuelles. De plus, ils peuvent fournir un aperçu de la biologie du cancer induit par le HPV et préconiser ainsi des pistes pour le développement de thérapies non chirurgicales. A titre d'exemples de marqueurs biologiques, il y a la cornuline, PA28 β, DJ-l, l'actine, la transthyrétine, HSPB1, le canal intracellulaire 1 du CV, la cytokératine 8, la transferrine, Hspβ6 (HSP20), l'aflatoxine réductase, le collagène α2 de type I, la créatine kinase B, la cytokératine 13, la GST II, PA28 α, le manganèse SOD, la lamine A/C, la serpine B1 (inhibiteur d'élastases), la serpine B3 (SCAA1), la cytokératine 10, la cytokératine 6A, et la trp-ARNt synthétase. Les marqueurs biologiques préférés pour le cancer induit par le HPV comprennent la cornuline, DJ-l, PA28 α, et PA28β, la trp-ARNt synthétase, Hspβ6, la créatine kinase B, l'aflatoxine réductase, la GST II, la transthyrétine, la transferrine, le collagène α2 de type I, et leurs combinaisons.
PCT/US2009/031302 2008-01-16 2009-01-16 Marqueurs biologiques pour le cancer induit par le hpv WO2009092017A1 (fr)

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EP2735874A1 (fr) * 2012-11-21 2014-05-28 Fundación Para La Investigación Biomédica Del Hospital Universitario Puerta De Hierro Procédés de diagnostic et agents thérapeutiques destinés à être utilisés dans le traitement du cancer de la prostate
US20160025729A1 (en) * 2014-07-25 2016-01-28 OncoGenesis Inc. Systems And Methods For Early Detection Of Cervical Cancer By Multiplex Protein Biomarkers
WO2016060557A1 (fr) * 2014-10-17 2016-04-21 Stichting Maastricht Radiation Oncology "Maastro-Clinic" Procédé d'analyse d'image aidant à la prévision de l'évolution d'une maladie pour un néoplasme dans un organisme humain ou animal
US10487365B2 (en) 2016-09-20 2019-11-26 The United States Of America, As Represented By The Secretary, Department Of Health And Human Services Methods for detecting expression of lnc-FANCI-2 in cervical cells

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